Analyzing passenger connectivity experiences while using vehicle cabin networks

ABSTRACT

A network analysis terminal is described that operates within a vehicle cabin to generate passenger connectivity experience metrics. The terminal monitors packets communicated through at least one cabin network between a content server and passenger terminals. The terminal receives packets monitored by the network interface and identifies passenger terminal identifiers that are addressed by content of the packets. Names of vehicle passengers associated with the packets are identified using the passenger terminal identifiers as indexes to retrieve the names of vehicle passengers from an information repository that maps names of vehicle passengers to passenger terminal identifiers. Passenger connectivity experience metrics are generated based on measurements performed on the packets over time. The passenger connectivity experience metrics indicate network connectivity performance that is experienced by the identified names of vehicle passengers while operating passenger terminals using the at least one cabin network.

TECHNICAL FIELD

The present disclosure relates to monitoring performance of vehicle communication systems, such as in-flight entertainment systems.

BACKGROUND

In-flight entertainment (IFE) systems are deployed onboard aircraft to provide entertainment services for passengers in a passenger cabin. The IFE systems typically provide passengers with television and audio multimedia entertainment programming.

One type of IFE system is a “server centric” architecture where multimedia content is located on a server or a set of servers installed in an electronic bay in the airplane. Video content is played through displays installed at overhead locations or within seatbacks, and associated audio content is played through jacks provided in seat armrests.

Another type of IFE system is a “seat centric” architecture where content is stored in mass data storage devices located at individual seats and played through associated seat displays. The server (or set of servers) acts as an injection point for content that will be later installed locally into the seat mass data storage devices, and also acts as a secondary source for content that may not fit in the seat mass data storage devices.

There has also been an emergence of wireless systems providing connectivity within server centric architectures and seat centric architectures to passenger personal electronic devices (PEDs) or “passenger terminals”, such as Internet access, as well as limited streaming entertainment, such as movies. These systems use servers to provide content through Cabin Wireless Access Points (CWAPs) installed at spaced apart locations along the airplane cabin.

With the proliferation of the number of different types of vehicle entertainment systems and associated cabin equipment along with the increasing use of a myriad of different types and configurations of terminals that are carried onboard by passengers, it is becoming increasingly difficult to assess whether such systems are performing acceptably and what is contributing to operational limitations or problems.

SUMMARY

Some embodiments of the present invention are directed to a network analysis terminal used within a vehicle cabin. The terminal includes a network interface which is configured to monitor packets communicated through at least one cabin network between a content server and passenger terminals. A processor is connected to receive packets monitored by the network interface, and is configured to identify passenger terminal identifiers that are addressed by content of the packets. Names of vehicle passengers associated with the packets are identified using the passenger terminal identifiers as indexes to retrieve the names of vehicle passengers from an information repository that maps names of vehicle passengers to passenger terminal identifiers. Passenger connectivity experience metrics are generated based on measurements performed on the packets over time. The passenger connectivity experience metrics indicate network connectivity performance that is experienced by the identified names of vehicle passengers while operating passenger terminals using the at least one cabin network. Communications through the at least one cabin network are controlled based on the passenger connectivity experience metrics.

These and other operations and methods disclosed herein can non-intrusively measure the experience of passengers utilizing one or more cabin networks within a vehicle. For a network provider (such as a manufacturer of IFE systems) or a passenger carrier (such an airline operator), how well the communication system is performing from particular passengers' perspectives is important for the success of the service. Moreover, the passenger owned terminals which are being used to interface to the cabin networks may be the source of performance limitations or problems. The passenger connectivity experience metrics can be used to effectively identify the source of system operational limitations or problems.

Other network analysis terminals and related methods and computer program products according to embodiments of the present disclosure will be or become apparent to one with skill in the art upon review of the following drawings and detailed description. It is intended that all such additional network analysis terminals, methods, and computer program products be included within this description and be protected by the accompanying claims. Moreover, it is intended that all embodiments disclosed herein can be implemented separately or combined in any way and/or combination.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings, which are included to provide a further understanding of the disclosure and are incorporated in and constitute a part of this application, illustrate certain non-limiting embodiment(s) of the invention. In the drawings:

FIG. 1 illustrates a network analysis terminal that generates passenger connectivity experience metrics based on measurements of packets communicated for an IFE system having cabin wireless access points (CWAPs) that interconnect seat video display units (SVDUs) and passenger terminals to a content server, in accordance with some embodiments;

FIG. 2 illustrates example serving cells provided by the CWAPs mounted to ceiling structure along an aisle of the aircraft cabin;

FIG. 2 is a block diagram of the CWAP server, the CWAPs, and the IFE content server of FIG. 1 configured according to some embodiments;

FIG. 3 is a block diagram of the IFE system of FIG. 1 configured according to some embodiments;

FIG. 4 is a combined flowchart and data flow diagram of operations and methods performed by a passenger terminal, a CWAP, and a content server according to some embodiments;

FIGS. 5-12 illustrate operations and methods performed by the network analysis terminal in accordance with some embodiments; and

FIG. 13 is a block diagram of a network node that can be configured to operate as the content server and/or a CWAP in accordance with some embodiments.

DETAILED DESCRIPTION

In the following detailed description, numerous specific details are set forth in order to provide a thorough understanding of aspects of the invention. However, it will be understood by those skilled in the art that the present invention may be practiced without these specific details. In other instances, well-known methods, procedures, components and circuits have not been described in detail so as not to obscure the present invention.

Although various embodiments are explained herein in the context of entertainment systems for an In-Flight Entertainment (IFE) environment of an aircraft, other embodiments are not limited thereto and may be used in other types of vehicles, including, without limitation, ships, buses, and trains. Thus reference to a vehicle cabin can correspond to the passenger space that is moved by any such vehicle.

Various embodiments of the present disclosure are directed to non-intrusively measuring the passenger (user) experience of one or more passengers utilizing one or more cabin networks within a vehicle. For a network provider (such as a manufacturer of IFE systems) or a passenger carrier (such an airline operator), how well the communication system is performing from particular passengers' perspectives is important for the success of the service. While the hardware platform(s) may be functioning properly, software components and other factors (such as RF interference in a wireless network) may still result in a poor passenger experience. Moreover, the passenger owned terminals which are being used to interface to the cabin networks may be the source of performance limitations or problems. The passenger connectivity experience metrics can be used to identify the source of such limitations or problems.

Known network analysis tools can operate within components of a communication network to query or monitor certain hardware and/or software performance metrics. However, the terminals carried on-board by passengers (“passenger terminals”) are not part of the cabin communication equipment and thus can't be effectively monitored. Hence, operational problems occurring within passenger terminals may not be effectively identified, measured, or analyzed.

Various operations and methods that can be performed to provide improved monitoring and analysis of passenger connectivity experiences with using one or more cabin networks are described below in the non-limiting context of an aircraft IFE environment.

FIG. 1 illustrates an IFE system that includes Cabin Wireless Access Points (CWAPs) 110 that are installed (mounted) at spaced apart locations along a passenger aisle within an aircraft cabin 100 to provide corresponding wireless communication service cells to seat Video Display Units (VDUs) or SVDUs 132, passenger terminals 130, and other types of wireless terminals. The CWAPs 110 communicate through a wireless air interface that can be operated based on one or more communication protocols including, without limitation, IEEE 802.11, 3GPP Long Term Evolution (LTE), Bluetooth, WIMAX, light WIFI, etc. Because embodiments of the present disclosure can be used in other environments, a CWAP can also be more generally referred to as a wireless access point (WAP).

The seat VDUs 132 may include displays that are mounted to seatbacks, to tray tables that are deployable from armrests, and/or to other seat structure or cabin structure. The passenger terminals 130 may correspond to any personal wireless terminal having wireless communications capabilities for communicating with the CWAPs and which can be carried by a passenger onto an aircraft, including, without limitation, tablet computers, laptop computers, palmtop computers, cellular smart phones, media players, etc. Embodiments of the present disclosure can be used with any plural number of CWAPs 110, seat VDUs 132, and passenger terminals 130, and are not limited to the example numbers shown in any of the figures.

The seat VDUs 132 and the passenger terminals 130 can be used by passengers for IFE services in which video and other content is wirelessly communicated from an IFE content server 132 via packets containing IP addresses of the seat VDUs 132 and/or passenger terminals 130. The packets are routed through the CWAPs 110 that provide wireless communication service to those seat VDUs 132 and/or passenger terminals 130. Passengers may also be provided in-flight shopping services through the seat VDUs 132 and the passenger terminals 130 based on product catalogs that are downloaded from the content server 140. The seat VDUs 132 and the passenger terminals 130 may also be provided Internet connectivity through the CWAPs 110 and an off-board radio link transceiver 120 (e.g., Satellite communication link, cellular communication link, etc.) to a ground based Internet or private network access edge router.

In accordance with various embodiments herein, the IFE system of FIG. 1 includes a network analysis terminal 150 that generates passenger connectivity experience metrics based on measurements of packets being communicated between the CWAPs 110 and the passenger terminals 130 and/or between the CWAPs 110 and the seat VDUs 132, and or may be connected to generate passenger connectivity experience metrics based on measurements of packets between the CWAPs 110 and the content server 132, in accordance with some embodiments.

The network analysis terminal 150 actively monitors network traffic between passenger terminals 130, seat VDUs 132, and/or other endpoints and the end services with which they are communicating (e.g., the content server 132 and/or the off-board radio link transceiver 120 to an off-board Internet server). Passenger connectivity experience metrics are generated that can be used to determine not just that the users are able to access the services, but also measure defined performance characteristics of those services. This provides significant insight into how those passengers perceive the quality of experience with using those services.

This network analysis terminal 150 can be tailored to monitor operations and performance of specific service end-points both internally (e.g., the content server 132 and/or the off-board radio link transceiver 120 to an off-board Internet server) and externally (e.g., website or content provided by networked web server).

The diagram above shows a typical cabin network in which passengers utilize various passenger terminals 130 (e.g., smart phones, tablet computers, laptop computers, etc.) that communicate via the CWAPs 110 and a backbone wired network (e.g., Ethernet). This cabin network typically can include local services such as network services (e.g., DHCP, DNS, and routing functional services). The off-board radio link transceiver 120, the content server 132, and/or another component can perform router operations that route passenger network traffic to on-board services or off-board to, e.g., the Internet to access web sites and/or services from third parties (e.g., Google or Amazon operated web servers).

The network analysis terminal 150 is positioned and configured to “hear” the bi-directional traffic flow between the passengers and the service points through the cabin network. This terminal 150 examines the network traffic flows between the passengers and the service points and performs qualitative measurements on the availability and performance of those communications. The terminal 150 may perform deep packet inspection to identify which on-board or off-board service is associated with the communication (e.g., streaming audio from Amazon web server) and/or which operational state of a protocol is being invoked by the packet. Optionally, results of the measurements can be fed back into the IFE system and/or components of the cabin network, and/or can be forwarded to a crew terminal and/or to a system operator console, which may be on-board or off-board, to improve and/or enhance the passenger's connectivity experience.

Various embodiments of the network analysis terminal 150 operate to detect devices using the cabin network and actively analyzes packet flows and/or related protocol transitions between each device and service end points. For example, in some systems there are specific known packet exchanges that are expected to be observed by the network analysis terminal 150 when the service end points and cabin network components are operating normally. These exchanges can be detected and analyzed, to determine whether the associated services are both available and have acceptable performance metrics compared to acceptable availability policies and performance rules. Quality of service can be measured, such as the timing jitter experienced between packets provided in a sequence for a service, error rate across the packets, packet retransmission rates due to errors or dropped packets, etc.

As part of the measurement process, both quality and performance attributes can be analyzed. The throughput and latency of the packet exchanges can be analyzed to detect if there is system degradation that satisfies a defined action rule which triggers an associated defined remediation action. Retransmissions of packets and/or flow control requests can be observed and measured to detect potential communication performance bottlenecks, presence of interfering passenger terminals, poorly operating passenger terminals, and other system communication issues.

The network analysis terminal 150 can be further enhanced and customized to analyze specific service requests, e.g., HTTP requests, to collect additional information about the passengers' behaviors and service end point usage patterns.

These operations and capabilities may, in some embodiment, be performed when communication traffic through the cabin network is encrypted. For example, the network analysis terminal 150 can observe and measure content of protocol information that is communicated as unencrypted data with encrypted user traffic packets. The network analysis terminal 150 can analyze data provided by Ethernet and TCP/IP layers, where data is not encrypted (except in some wireless networks). In some embodiments, the network analysis terminal 150 is provided necessary encryption information to allow decryption of network packets that are encrypted by the service end points and/or by components of the cabin network.

In some embodiments, the network analysis terminal 150 interacts with passenger terminals 130 and/or other end point devices in a listen/receive only mode, so that there is no inherent additional impact on the cabin network performance and operation. The terminal 150 can analyze the network packet traffic in “real-time” and compute passenger connectivity experience metrics related to each passenger terminal and the related specific behaviors of different passengers. As explained above, the generated passenger connectivity experience metrics can be optionally fed back to control operation of the IFE system and/or components of the cabin network, and/or can be forwarded to a crew terminal and/or to a system operator console.

Although the network analysis terminal 150 is illustrated as being separate from the content server 132 and components of the cabin network, it may in some other embodiments be at least partially incorporated into the content server 132, a CWAP 110, or another component of the cabin network. The network analysis terminal 150 can be a stand-alone tablet computer particularly configured to perform one or more of the embodiments disclosed herein. It may be desirable to host operations of the network analysis terminal 150 as close to the passenger's environment as possible, so that the terminal operations can analyze as much traffic as possible between the passenger terminals 130 and service points.

The network analysis terminal 150 can include a wireless network interface configured to listen to packets communicated through a wireless air interface and/or may have a “wired” network interface to a wired network (e.g., Ethernet or other wired LAN). However, if the terminal 150 only has a wired network interface it may be difficult or not possible to detect issues within the “wireless” network (such as interference). The network analysis terminal 150 can include multiple network interfaces (wired and/or wireless) that operate to simultaneously monitor multiple networks and/or network access points, e.g., CWAPs 110.

Additional (external) sensors could be added to capture additional data items to enhance the types passenger connectivity experience metrics that can be generated and the accuracy of those metric. Some such sensors may include items such as: time sources, Radio Frequency sensors (for WiFi type networks), etc.

FIG. 2 illustrates example serving cells 200, 202, 204 provided by the CWAPs 110 (FIG. 1) mounted to ceiling structure along an aisle of the aircraft cabin 100. The network analysis terminal 150 may be movable along the aisle through the serving cells 200, 202, 204 by a crew member and/or other operator to perform measurements of packets being communicated between the respective CWAPs 110 and the passenger terminals 130, seat VDUs 132, and/or other communication terminals.

FIG. 3 is a block diagram of the IFE system and network analysis terminal of FIG. 1 configured according to some embodiments. The system includes a content server 132 that communicates with passenger terminals, not shown, via a cabin network 300. The illustrated cabin network 300 includes CWAPs 110 (e.g., CWAP_1, CWAP_2, and CWAP_3). CWAP_1 and CWAP_2 are serially connected to Port 1 of the content server 132 via Ethernet segments 302 a and 302 b. In contrast, CWAP_3 is connected to Port 2 of the content server 132 via Ethernet segment 302 c. The network analysis terminal 150 can be configured to monitor the wireless air interface used by the cabin network 300 and/or can be connected to one or more of the Ethernet segments 302 to receive packets communicated between two or more of: the content server 132; the CWAPs 110; the passenger terminals 130; the seat VDUs 132; and/or other components of the IFE system.

In the illustrated example, the content server 132 includes a Dynamic Host Configuration Protocol (DHCP) server 142, Some or all of the CWAPs 110, the passenger terminals 130, the network analysis terminal 150, and other devices that communicate with the content server 132 can include a DHCP client 112. A device uses the DHCP client 112 to acquire from the DHCP server 142 an IP address used to address communications to that device when communicating through the cabin network 300. In an IFE environment, the DHCP server 142 may maintain a configuration file that contains mapping between defined IP addresses and physical locations where the CWAPs 110 are installed, and may select among the defined IP addresses for assignment to a CWAP 110 based on a physical location of the CWAP 110.

The content server 132 can include a content streaming and File Transfer Protocol (FTP) controller 144 that provides content, such as a movies, television programs, electronic books and magazines, audio, games, etc., to seat VDUs 132 and passenger terminals 130. Some content may be streamed, e.g., movies, via a streaming protocol responsive to on-demand requests initiated by passengers, while other content, e.g., games, may be transferred as files via FTP.

The network analysis terminal 150 includes a network interface 158, a processor 152, and a memory 154. The network interface 158 may include a wired network interface (e.g., Ethernet, USB, etc.) and/or a wireless transceiver interface (e.g., IEEE 802.11, LTE, Bluetooth, WIMAX, Light WIFI, etc.). The terminal 150 can use its wireless transceiver interface to receive and decode packets that are being communicated through a wireless air interface between one or more of the CWAP 110 and one or more of the passenger terminals 130, the seat VDUs 132, etc.

The processor 152 may include one or more data processing circuits, such as a general purpose and/or special purpose processor (e.g., microprocessor and/or digital signal processor) that may be collocated or distributed across one or more networks. The processor 152 is configured to execute computer readable program code in the memory 154, described below as a non-transitory computer readable medium.

The memory 154 can include program code that performs some or all of the operations and methods that are described herein for one or more of the embodiments of a network analysis terminal. The memory 154 can include a DHCP client 112 and a mapping information repository 156 that contains information used to map names of vehicle passengers to passenger terminal identifiers, e.g., MAC addresses. The mapping repository 156 may include information 160 mapping media access control (MAC) addresses to passenger names, an electronic passenger manifest 162 mapping passenger names to seat numbers, and an electronic set of passenger itineraries 164 mapping passenger names to multi-vehicle travel legs. The electronic passenger manifest 162 can logically associate MAC addresses with passenger names and assigned seat numbers within the vehicle. The set of passenger itineraries 164 can logically associate the vehicle passengers with vehicle identifiers for vehicles that are scheduled to transport the respective vehicle passengers during multi-vehicle travel legs of respective trips.

Example operations that can be performed by the network analysis terminal 150 to generate passenger connectivity experience metrics and identify a problematic communication sequence as explained with reference to FIGS. 4 and 5. FIG. 4 is a combined flowchart and data flow diagram of operations and methods performed by a passenger terminal 130, a CWAP 110, and a content server 132 according to some embodiments. FIG. 5 illustrates operations and methods performed by the network analysis terminal 150 in accordance with some embodiments.

Referring to FIG. 4, the passenger terminal 130 performs the Dynamic Host Configuration Protocol (DHCP) operations through communications with the CWAP 110, and the DHCP server 142, to request Internet Protocol (IP) parameters, including assignment of an IP address thereto. The DHCP clients and server employ a connectionless service model, using the User Datagram Protocol (UDP).

The network analysis terminal 150 observes that the passenger terminal 130 has transmitted (block 400) a DHCP discovery message packet, which is an IP address lease request. The terminal 150 also observes that the CWAP 110 has transmitted (block 402) a DHCP offer message packet toward the passenger terminal 150 responsive to the DHCP discovery message. The terminal 150 subsequently observes repeated duplication of the cycle of packet transmissions of DHCP discovery messages and responsive DHCP offer messages between the passenger terminal 130 and the CWAP 110, including the passenger terminal 130 transmission (block 404) and the CWAP 110 responsive transmission (block 406).

The network analysis terminal 150 thereby identifies occurrences of the passenger terminal identifier (e.g., MAC address) of the passenger terminal 130 repeatedly sending DHCP discovery messages through the cabin network 300 while apparently ignoring responsive DHCP offer messages from the cabin network 300, and operates to generate a passenger connectivity experience metric based on the identified occurrences. The passenger connectivity experience metric can indicate that the passenger terminal 130 is not properly operating when performing the DHCP protocol, and may identify the name of the passenger who is known to be associated with the passenger terminal identifier and may identify characteristics of the passenger terminal 130 based on content of those observed packets. The identified characteristics of the passenger terminal 130 can include the type of operating system hosted by the terminal 130, the operating system version, the hardware terminal type, the manufacturer identifier (e.g., based on known MAC address ranges known to have been assigned to different terminal manufacturers), etc., which may be determined based on deep packet inspection of content of the observed packets.

The network analysis terminal 150 continues monitoring packets transmitted through the wireless air interface and observes a further DHCP request message packet transmitted (block 408) by the passenger terminal 130 and a responsive DHCP acknowledgment message transmitted (block 410) by the CWAP 110, indicating that the passenger terminal 130 has finally accepted the transmitted (block 406) DHCP offer message. The terminal 150 subsequently monitors packets communicated between the passenger terminal 130 and the CWAP 110 as content is requested by the passenger terminal 130 and responsively streamed from the content server 132 through the CWAP 110. More particularly, the terminal 150 can observe content streaming request messages transmitted (block 412) by the passenger terminal 130 and observe responsive content packets streamed (block 416). Terminal 150 can further observe acknowledgments transmitted (block 412) by the passenger terminal 130 responsive to receiving, decoding, and performing acceptable error-checking on the received content packets, and can observe automatic request (ARQ) retransmission of content packets by the content server 132 responsive to absence of ARQ packets from the passenger terminal 130 within a threshold timeframe of the corresponding content packet transmission. The CWAP 110 forwards (block 414) packets received through the wireless air interface from the passenger terminal 130 toward the addressed content server 132, and similarly forwards packets received through the wireless air interface from the content server 132 toward the addressed passenger terminal 130.

With further reference to FIG. 5, the network analysis terminal 150 monitors (block 500) message packets being communicated through the wireless air interface of the cabin network 300. The terminal 150 identifies (block 502) passenger terminal identifiers that are addressed by content of the packets. The terminal 150 identifies (block 504) names of vehicle passengers associated with the packets using the passenger terminal identifiers as indexes to retrieve the names of vehicle passengers from the information repository 160 that maps names of vehicle passengers to passenger terminal identifiers. The terminal 150 performs measurements (block 506) on the packets over time. Various measurements that can be performed by the terminal 150 are explained in further detail below. The terminal 150 generates (block 508) passenger connectivity experience metrics based on the measurements. The passenger connectivity experience metrics indicate network connectivity performance experienced by the identified names of vehicle passengers while operating passenger terminals using the cabin network 300. The terminal 150 controls (block 510) communications through the cabin network 300 based on the passenger connectivity experience metrics, and may report (block 512) the connectivity experience metrics to another component of the cabin network 300, a crew terminal, an operator computer may be an-board or off-board the aircraft, etc.

The network analysis terminal 150 may operate to identify names of vehicle passengers associated with the packets, by receiving a message through the network interface 158 from an application executed by one of the passenger terminals 130 that stores a boarding pass and/or a reservation confirmation for one of the vehicle passengers, the message containing the name of the one of the vehicle passengers and a MAC address for a network interface circuit of the one of the passenger terminals. The terminal 150 then stores the name of the one of the vehicle passengers and the MAC address with a logical association to each other within the information repository 160 in a memory.

The network analysis terminal 150 may operate to generating a passenger connectivity experience metric for one of the identified names of a vehicle passenger based on measurements performed on a series of packets that each contain an address for one of passenger terminal identifiers that is identified from the information repository 160 as being associated with the identified name of the vehicle passenger, while excluding from the generation of the passenger connectivity experience metric for the one of the identified names any measurements performed on packets that do not contain the address for the one of passenger terminal identifiers that is identified as associated with the identified name of the vehicle passenger. Thus, for example, the metric can generated based measurements performed on only packets that contain the MAC address for a particular one of the passenger terminals 140. The metric thereby represents the network connectivity experience of one passenger who is operating the particular terminal.

In some embodiments, the operations for identifying passenger terminal identifiers that are addressed by content of the packets, include identifying MAC addresses for network interface circuits 158 of the passenger terminals 140. The operations for identifying names of vehicle passengers associated with the packets using the passenger terminal identifiers as indexes to retrieve the names of vehicle passengers from the information repository 160, can include querying the information repository 160 to identify one of the passenger names that is logically associated with one of the MAC addresses that has been identified as content of one of the packets observed by the terminal 150.

The network analysis terminal 150 can operate to generate the passenger connectivity experience metric, based on obtaining an electronic passenger itinerary, e.g., from the set of passenger itineraries 164, that logically associates the identified name of the vehicle passenger with vehicle identifiers for vehicles that are scheduled to transport the vehicle passenger during multi-vehicle travel legs of a trip. The terminal 150 can update the passenger connectivity experience metric responsive to receipt of further packets associated with the identified name of the vehicle passenger during the duration of a present one of the multi-vehicle travel legs of the trip, and store the updated passenger connectivity experience metric in the electronic passenger itinerary repository 164 with a logical association to the identified name of the vehicle passenger and a logical association to the vehicle identifier for the vehicle. Thus, metrics can be generated over multiple legs of flights of different aircraft, with the resulting metrics being stored in a repository that can be transferred from one aircraft to another aircraft via a ground datalink network interface, an aircraft-to-aircraft datalink network, and/or storing the metrics on the respective passenger terminals 140 for transport by passengers between the aircraft.

Various further embodiments related to how the network analysis terminal 150 can generate passenger connectivity experience metrics are now described in the context of the operational flowcharts of FIGS. 6-11.

In the embodiment of FIG. 7, the network analysis terminal 150 may operate to decode (block 700) the packets, identify (block 702) a bit error rate occurring in the decoded packets that contain the address for the one of passenger terminal identifiers that is identified as associated with the identified name of the vehicle passenger, and then generate (block 704) the passenger connectivity experience metric based on the bit error rate. Accordingly, the metric can indicate the bit error rate being experienced by communications with one particular passenger via the cabin network 300, which may be affected by problematic operations performed by the particular passenger's terminal, e.g., as described for FIG. 4.

In the embodiment of FIG. 8, the network analysis terminal 150 may operate to count (block 800) a number of packet retransmission requests sent by the one of passenger terminal identifiers that is identified as associated with the identified name of the vehicle passenger, and generate (block 802) the passenger connectivity experience metric based on the number of packet retransmission requests. Accordingly, the metric can indicate the packet retransmission rate being experienced by communications with one particular passenger via the cabin network 300, which may be similarly affect by problematic operations performed by the particular passenger's terminal, e.g., as described for FIG. 4.

In the embodiment of FIG. 9, the network analysis terminal 150 may operate to determine (block 900) communication bandwidth (e.g., effective packet communication data rate) over a time interval of data communicated in packets sent by the one of passenger terminal identifiers that is identified as associated with the identified name of the vehicle passenger, and generate (block 902) the passenger connectivity experience metric based on the bandwidth. Accordingly, the metric can indicate the communication bandwidth experienced by one particular passenger while communicating through the cabin network 300.

In the embodiment of FIG. 10, the network analysis terminal 150 may operate to identify (block 1000) occurrences of the one of passenger terminal identifiers, that is identified as associated with the identified name of the vehicle passenger, transmitting wireless signals having signal strength below a defined threshold level toward a CWAP 110 of the cabin network 300, and generate (block 1002) the passenger connectivity experience metric based on the identified occurrences. Accordingly, the metric may indicate whether an identified passenger is possibly having an unsatisfactory experience using the cabin network 300 due to the passenger's terminal 130 transmitting with insufficient signal strength to be reliably received by the CWAP 110 in view of interference and/or other factors affecting the communication channel.

In the embodiment of FIG. 11, the network analysis terminal 150 may operate to identify (block 1000) occurrences of the one of passenger terminal identifiers, that is identified as associated with the identified name of the vehicle passenger, not properly performing a defined message handshake with a CWAP 110 of the cabin network 300. The terminal 150 can generate (block 1002) the passenger connectivity experience metric based on the identified occurrences. An example of one improper message handshake observable by the terminal 150 was described with regarding to FIG. 4. The terminal 150 can identify the name of a particular passenger who may be experiencing degraded network connection performance due to such improper handshaking by the passenger's terminal 140.

For example, as explained above, the network analysis terminal 150 may identify occurrences of a passenger terminal identifier, that is identified as associated with an identified name of the vehicle passenger, repeatedly sending DHCP discovery messages toward the cabin network 300 while apparently ignoring responsive DHCP offer messages from the cabin network 300, and can generate the passenger connectivity experience metric based on the identified occurrences. The terminal 150 may respond to determining that the passenger connectivity experience metric satisfies a defined remedial action rule, by sending a message to one or more of the CWAPs 110 instructing to block establishment of a communication link to the one of passenger terminal identifiers.

Various actions that can be performed by the network analysis terminal 150 to control communications through the cabin network 300 and/or to report the passenger connectivity experience metrics are now described with reference to the operational flowchart of FIG. 12.

In some embodiments, the network analysis terminal 150 operates to identify (block 1200) occurrences of the one of passenger terminal identifiers, that is identified as associated with the identified name of the vehicle passenger, causing at least a threshold level of interference to communications between a CWAP 110 of the cabin network 300 and other passenger terminals 140, and generates the passenger connectivity experience metric based on the identified occurrences. The terminal 150 then operates to control (block 1202) communications through the cabin network 300 by, responsive to the passenger connectivity experience metric satisfying a defined remedial action rule, sending (block 1204) a message to the CWAP 110 to block establishment of a communication link to the one of passenger terminal identifiers.

In a further or alternate embodiment, the terminal 150 responds to the passenger connectivity experience metric satisfying a defined remedial action rule, by querying (block 1206) the electronic passenger manifest 162, which logically associates passenger names with cabin seat identifiers, to identify one of the cabin seat identifiers where the identified name of the vehicle passenger is located. The terminal 150 then sends (block 1208) to a crew terminal a notification message that contains the identified one of the cabin seat identifiers and an indication that excessive interference by that passenger to the cabin network 300 is occurring.

FIG. 13 is a block diagram of a network node 1300 that can be configured to operate as a content server 132 and/or as a CWAP 110 in accordance with some embodiments. The network node 1300 includes a processor 1302, a memory 1304, and a wired network interface 1306 and/or a radio transceiver network interface 1308. The processor 1302 may include one or more data processing circuits, such as a general purpose and/or special purpose processor (e.g., microprocessor and/or digital signal processor) that may be collocated or distributed across one or more networks. The processor 1302 is configured to execute computer readable program code in the memory 1304, described below as a non-transitory computer readable medium, to perform some or all of the operations and methods that are described herein for a content server 132 and/or a CWAP 110.

Further Definitions and Embodiments

In the above-description of various embodiments of the present disclosure, it is to be understood that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of this specification and the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.

When an element is referred to as being “connected”, “coupled”, “responsive”, or variants thereof to another element, it can be directly connected, coupled, or responsive to the other element or intervening elements may be present. In contrast, when an element is referred to as being “directly connected”, “directly coupled”, “directly responsive”, or variants thereof to another element, there are no intervening elements present. Like numbers refer to like elements throughout. Furthermore, “coupled”, “connected”, “responsive”, or variants thereof as used herein may include wirelessly coupled, connected, or responsive. As used herein, the singular forms “a”, “an” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. Well-known functions or constructions may not be described in detail for brevity and/or clarity. The term “and/or” includes any and all combinations of one or more of the associated listed items.

As used herein, the terms “comprise”, “comprising”, “comprises”, “include”, “including”, “includes”, “have”, “has”, “having”, or variants thereof are open-ended, and include one or more stated features, integers, elements, steps, components or functions but does not preclude the presence or addition of one or more other features, integers, elements, steps, components, functions or groups thereof. Furthermore, as used herein, the common abbreviation “e.g.”, which derives from the Latin phrase “exempli gratia,” may be used to introduce or specify a general example or examples of a previously mentioned item, and is not intended to be limiting of such item. The common abbreviation “i.e.”, which derives from the Latin phrase “id est,” may be used to specify a particular item from a more general recitation.

Example embodiments are described herein with reference to block diagrams and/or flowchart illustrations of computer-implemented, methods, apparatus (systems and/or devices) and/or computer program products. It is understood that a block of the block diagrams and/or flowchart illustrations, and combinations of blocks in the block diagrams and/or flowchart illustrations, can be implemented by computer program instructions that are performed by one or more computer circuits. These computer program instructions may be provided to a processor circuit of a general purpose computer circuit, special purpose computer circuit, and/or other programmable data processing circuit to produce a machine, such that the instructions, which execute via the processor of the computer and/or other programmable data processing apparatus, transform and control transistors, values stored in memory locations, and other hardware components within such circuitry to implement the functions/acts specified in the block diagrams and/or flowchart block or blocks, and thereby create means (functionality) and/or structure for implementing the functions/acts specified in the block diagrams and/or flowchart block(s).

These computer program instructions may also be stored in a non-transitory computer-readable medium that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable medium produce an article of manufacture including instructions which implement the functions/acts specified in the block diagrams and/or flowchart block or blocks.

A non-transitory computer-readable medium may include an electronic, magnetic, optical, electromagnetic, or semiconductor data storage system, apparatus, or device. More specific examples of the computer-readable medium would include the following: a portable computer diskette, a random access memory (RAM) circuit, a read-only memory (ROM) circuit, an erasable programmable read-only memory (EPROM or Flash memory) circuit, a portable compact disc read-only memory (CD-ROM), and a portable digital video disc read-only memory (DVD/BlueRay).

The computer program instructions may also be loaded onto a computer and/or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer and/or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions/acts specified in the block diagrams and/or flowchart block or blocks. Accordingly, embodiments of the present disclosure may be embodied in hardware and/or in software (including firmware, resident software, micro-code, etc.) that runs on a processor such as a digital signal processor, which may collectively be referred to as “circuitry,” “a module” or variants thereof.

It should also be noted that in some alternate implementations, the functions/acts noted in the blocks may occur out of the order noted in the flowcharts. For example, two blocks shown in succession may in fact be executed substantially concurrently or the blocks may sometimes be executed in the reverse order, depending upon the functionality/acts involved. Moreover, the functionality of a given block of the flowcharts and/or block diagrams may be separated into multiple blocks and/or the functionality of two or more blocks of the flowcharts and/or block diagrams may be at least partially integrated. Finally, other blocks may be added/inserted between the blocks that are illustrated. Moreover, although some of the diagrams include arrows on communication paths to show a primary direction of communication, it is to be understood that communication may occur in the opposite direction to the depicted arrows.

Many different embodiments have been disclosed herein, in connection with the above description and the drawings. It will be understood that it would be unduly repetitious and obfuscating to literally describe and illustrate every combination and subcombination of these embodiments. Accordingly, the present specification, including the drawings, shall be construed to constitute a complete written description of various example combinations and subcombinations of embodiments and of the manner and process of making and using them, and shall support claims to any such combination or subcombination.

Many variations and modifications can be made to the embodiments without substantially departing from the principles of the present invention. All such variations and modifications are intended to be included herein within the scope of the present invention. 

What is claimed is:
 1. A network analysis terminal within a vehicle cabin, the network analysis terminal comprising: a network interface configured to monitor packets communicated through at least one cabin network between a content server and passenger terminals; a processor connected to receive packets monitored by the network interface; and a memory connected to the processor and storing computer readable program code executed by the processor to perform operations comprising: identifying passenger terminal identifiers that are addressed by content of the packets; identifying names of vehicle passengers associated with the packets using the passenger terminal identifiers as indexes to retrieve the names of vehicle passengers from an information repository that maps names of vehicle passengers to passenger terminal identifiers; generating passenger connectivity experience metrics based on measurements performed on the packets over time, the passenger connectivity experience metrics indicating network connectivity performance experienced by the identified names of vehicle passengers while operating passenger terminals using the at least one cabin network; and controlling communications through the at least one cabin network based on the passenger connectivity experience metrics.
 2. The network analysis terminal of claim 1, wherein: the at least one cabin network comprises cabin wireless access points that are attached to structure of the vehicle at spaced apart locations along a cabin of the vehicle and are communicatively connected to the content server; the network analysis terminal comprises a mobile communication terminal; and the network interface of the mobile communication terminal is configured to receive and decode packets being communicated through a wireless air interface between the cabin wireless access points and the passenger terminals.
 3. The network analysis terminal of claim 1, wherein the operations for identifying names of vehicle passengers associated with the packets using the passenger terminal identifiers as indexes to retrieve the names of vehicle passengers from an information repository that maps names of vehicle passengers to passenger terminal identifiers, comprise: receiving a message through the network interface from an application executed by one of the passenger terminals that stores a boarding pass and/or a reservation confirmation for one of the vehicle passengers, the message containing the name of the one of the vehicle passengers and a Media Access Control address for a network interface circuit of the one of the passenger terminals; and storing the name of the one of the vehicle passengers and the Media Access Control address with a logical association to each other within the information repository in the memory.
 4. The network analysis terminal of claim 1, wherein the operations for generating passenger connectivity experience metrics based on measurements performed on the packets over time, comprise: generating a passenger connectivity experience metric for one of the identified names of a vehicle passenger based on measurements performed on a series of packets that each contain an address for one of passenger terminal identifiers that is identified from the information repository as associated with the identified name of the vehicle passenger, while excluding from the generation of the passenger connectivity experience metric for the one of the identified names any measurements performed on packets that do not contain the address for the one of passenger terminal identifiers that is identified as associated with the identified name of the vehicle passenger.
 5. The network analysis terminal of claim 1, wherein: the operations for identifying passenger terminal identifiers that are addressed by content of the packets, comprise identifying Media Access Control addresses for network interface circuits of the passenger terminals; and the information repository logically associates Media Access Control addresses with passenger names; and the operations for identifying names of vehicle passengers associated with the packets using the passenger terminal identifiers as indexes to retrieve the names of vehicle passengers from an information repository that maps names of vehicle passengers to passenger terminal identifiers, comprises querying the information repository to identify one of the passenger names that is logically associated with one of the Media Access Control addresses that has been identified.
 6. The network analysis terminal of claim 5, wherein: the information repository comprises an electronic passenger manifest that logically associates passenger names to assigned seat numbers within the vehicle.
 7. The network analysis terminal of claim 5, wherein the operations for generating the passenger connectivity experience metric, further comprise: obtaining an electronic passenger itinerary that logically associates the identified name of the vehicle passenger with vehicle identifiers for vehicles that are scheduled to transport the vehicle passenger during multi-vehicle travel legs of a trip; updating the passenger connectivity experience metric responsive to receipt of further packets associated with the identified name of the vehicle passenger during the duration of a present one of the multi-vehicle travel legs of the trip; and storing the updated passenger connectivity experience metric in the electronic passenger itinerary with a logical association to the identified name of the vehicle passenger and a logical association to the vehicle identifier for the vehicle.
 8. The network analysis terminal of claim 5, wherein the operations for generating a passenger connectivity experience metric, further comprise: operating the network analysis terminal to decode the packets; identify a bit error rate occurring in the decoded packets that contain the address for the one of passenger terminal identifiers that is identified as associated with the identified name of the vehicle passenger; and generating the passenger connectivity experience metric based on the bit error rate.
 9. The network analysis terminal of claim 5, wherein the operations for generating a passenger connectivity experience metric, further comprise: counting a number of packet retransmission requests sent by the one of passenger terminal identifiers that is identified as associated with the identified name of the vehicle passenger; and generating the passenger connectivity experience metric based on the number of packet retransmission requests.
 10. The network analysis terminal of claim 5, wherein the operations for generating a passenger connectivity experience metric, further comprise: determining communication bandwidth over a time interval of data communicated in packets sent by the one of passenger terminal identifiers that is identified as associated with the identified name of the vehicle passenger; and generating the passenger connectivity experience metric based on the bandwidth.
 11. The network analysis terminal of claim 5, wherein the operations for generating a passenger connectivity experience metric, further comprise: identifying occurrences of the one of passenger terminal identifiers, that is identified as associated with the identified name of the vehicle passenger, transmitting wireless signals having signal strength below a defined threshold level toward a cabin wireless access point of the at least one cabin network; and generating the passenger connectivity experience metric based on the identified occurrences.
 12. The network analysis terminal of claim 5, wherein the operations for generating a passenger connectivity experience metric, further comprise: identifying occurrences of the one of passenger terminal identifiers, that is identified as associated with the identified name of the vehicle passenger, not properly performing a defined message handshake with a cabin wireless access point of the at least one cabin network; and generating the passenger connectivity experience metric based on the identified occurrences.
 13. The network analysis terminal of claim 12, wherein the operations for identifying occurrences of the one of passenger terminal identifiers, that is identified as associated with the identified name of the vehicle passenger, not properly performing a defined message handshake with a cabin wireless access point of the at least one cabin network, comprise: identifying occurrences of the one of passenger terminal identifiers, that is identified as associated with the identified name of the vehicle passenger, repeatedly sending Dynamic Host Configuration Protocol (DHCP) discovery messages through the at least one cabin network while ignoring responsive DHCP offer messages from the at least one cabin network; and generating the passenger connectivity experience metric based on the identified occurrences.
 14. The network analysis terminal of claim 12, wherein the operations for controlling communications through the at least one cabin network based on the passenger connectivity experience metrics, comprise: responsive to the passenger connectivity experience metric satisfying a defined remedial action rule, sending a message to the cabin wireless access point to block establishment of a communication link to the one of passenger terminal identifiers.
 15. The network analysis terminal of claim 5, wherein the operations for generating a passenger connectivity experience metric, further comprise: identifying occurrences of the one of passenger terminal identifiers, that is identified as associated with the identified name of the vehicle passenger, causing at least a threshold level of interference to communications between a cabin wireless access point of the at least one cabin network and other passenger terminals; generating the passenger connectivity experience metric based on the identified occurrences.
 16. The network analysis terminal of claim 15, wherein the operations for controlling communications through the at least one cabin network based on the passenger connectivity experience metrics, comprise: responsive to the passenger connectivity experience metric satisfying a defined remedial action rule, sending a message to the cabin wireless access point to block establishment of a communication link to the one of passenger terminal identifiers.
 17. The network analysis terminal of claim 15, wherein the operations for controlling communications through the at least one cabin network based on the passenger connectivity experience metrics, comprise: responsive to the passenger connectivity experience metric satisfying a defined remedial action rule, querying an electronic passenger manifest that logically associates passenger names with cabin seat identifiers to identify one of the cabin seat identifiers where the identified name of the vehicle passenger is located; and sending to a crew terminal a notification message that contains the identified one of the cabin seat identifiers and an indication that excessive interference by that passenger to the at least one cabin network is occurring.
 18. A method by a network analysis terminal within a vehicle cabin, the method comprising: monitoring packets communicated through at least one cabin network between a content server and passenger terminals; identifying passenger terminal identifiers that are addressed by content of the packets; identifying names of vehicle passengers associated with the packets using the passenger terminal identifiers as indexes to retrieve the names of vehicle passengers from an information repository that maps names of vehicle passengers to passenger terminal identifiers; generating passenger connectivity experience metrics based on measurements performed on the packets over time, the passenger connectivity experience metrics indicating network connectivity performance experienced by the identified names of vehicle passengers while operating passenger terminals using the at least one cabin network; and controlling communications through the at least one cabin network based on the passenger connectivity experience metrics.
 19. The method of claim 18, wherein the generating passenger connectivity experience metrics based on measurements performed on the packets over time, comprises: generating a passenger connectivity experience metric for one of the identified names of a vehicle passenger based on measurements performed on a series of packets that each contain an address for one of passenger terminal identifiers that is identified from the information repository as associated with the identified name of the vehicle passenger, while excluding from the generation of the passenger connectivity experience metric for the one of the identified names any measurements performed on packets that do not contain the address for the one of passenger terminal identifiers that is identified as associated with the identified name of the vehicle passenger.
 20. The method of claim 18, wherein: the identifying passenger terminal identifiers that are addressed by content of the packets, comprises identifying Media Access Control addresses for network interface circuits of the passenger terminals; the information repository logically associates Media Access Control addresses with passenger names; and the identifying names of vehicle passengers associated with the packets using the passenger terminal identifiers as indexes to retrieve the names of vehicle passengers from an information repository that maps names of vehicle passengers to passenger terminal identifiers, comprises querying the information repository to identify one of the passenger names that is logically associated with one of the Media Access Control addresses that has been identified. 